Tonika Reddy

Education AI Suite – Smart Classroom: Developed end-to-end AI pipelines for transcription and summarization (ASR + LLM). Benchmarked models based on accuracy and latency for optimal selection. Integrated seamless pipeline workflows across transcription and summarization stages.

AI Software Engineer Intern - Intel Technology Pvt. Ltd. - Bangalore

(2025-06 - 2026-06)

• Education AI Suite – Smart Classroom: Developed end-to-end AI pipelines for transcription and summarization (ASR + LLM).
• Benchmarked models based on accuracy and latency for optimal selection.
• Integrated seamless pipeline workflows across transcription and summarization stages.
• Implemented NPU-based execution for hardware acceleration.
• Built system metrics monitoring (CPU, GPU, NPU, memory, power).
• Enhanced pipeline with real-time audio preprocessing.
• Health AI Suite – Multi-Modal Patient Monitoring: Designed a multi-modal AI system integrating AI-ECG, rPPG, 3D pose, and MDPnP data.
• Developed frontend and backend for AI-ECG module with real-time waveform visualization.
• Built microservices-based architecture for real-time ingestion and processing.
• Enabled concurrent execution on CPU, GPU, and NPU.
• Implemented Docker containerization and Helm-based deployment.
• Developed a unified dashboard for vitals and system metrics.
• Retail AI Suite – Order Accuracy: Developed backend workflows for VLM-based item verification.
• Processed videos for frame extraction and optimization.
• Implemented frame selection and MinIO storage integration.
• Validated and optimized end-to-end pipeline performance.
• Store-wide Loss Prevention – Suspicious Activity Detection: Owned SceneScape integration and pipeline setup.
• Built real-time system using MQTT-based event streaming.
• Developed and integrated POC into production workflow.
• Presented live demos for team understanding and adoption.
• Built backend using FastAPI, REST APIs, and SeaweedFS.
• Currently working on stream density benchmarking for scalability analysis.
• System Validation & Performance Engineering: Performed fuzz testing using RESTler for API robustness.
• Improved system reliability, fault tolerance, and performance.
• Conducted latency, throughput, and resource utilization analysis.

Data Science Intern - Upskills (Edunet Foundation)

(2024-12 - 2025-01)

• Worked on data visualization and ML concepts.
• Built crop and weed detection system.
• Applied preprocessing and model evaluation.

Cyber Security Intern - Prowork Foundation (AICTE)

(2023-11 - 2024-04)

• Worked on cybersecurity fundamentals and networking.
• Built Network Intrusion Detection System (Python).
• Implemented packet analysis and anomaly detection.

M.Tech - Data Science - Manipal Institute of Technology

B.Tech - Computer Science and Engineering - Annamacharya Institute of Technology and Sciences